It is well known that petrophysical, compositional and geological evaluation of formations from which commodities from beneath the ground are desired to be extracted is a very important task. This is desirable partly so that an assessment can be made of the quantity and quality, and hence the value, of the materials in question; and also because it is important to know whether the extraction of such materials is likely to be problematic.
It is also well known that shoulder beds can have a large impact on estimates of petrophysical and compositional properties of formations. This is particularly true for thinly bedded formations. For example, it has been shown that shoulder-bed effects can cause errors in estimates of porosity, permeability and fluid concentrations in thin beds. Contrast in physical properties of adjacent beds is one of the most important shoulder-bed factors affecting formations. As such, it is important to accurately detect bed boundaries and intelligently account for inherent errors in any such detected bed boundaries.
Detection of bed boundaries can be done by evaluation of wellbore logs. In particular, wellbore image logs and core logs have been used in the past to help in detecting bed boundaries.
One of the techniques used commonly to compute petrophysical properties from logs is known as inversion. In this technique, certain data that may pertain to a log is used to predict the petrophysical properties of earth formations by taking account of known response characteristics of the logging tool.
Though various techniques have been used in the past for the inversion of petrophysical properties from wellbore logs, many of these techniques lack the level of accuracy desired, particularly when the beds are thinner than the innate resolution of the logs and do not provide adequate means for analyzing the associated inversion uncertainty. The following disclosure addresses these and other issues.